Conventionally, an image collation device for comparing and collating an input two-dimensional image with a previously recorded two-dimensional image has been practically used. In particular, various image collation devices for realizing a face authentication method that is one of the authentication methods using biometrics have been proposed. In image collation devices for realizing a face authentication method, face images of a plurality of persons who can be authenticated (hereinafter, referred to as “registered persons”) are previously registered in a database as registered face images. A face image of a person who is to be provided with authentication (hereinafter, referred to as “a person to be authenticated”) and a registered face image are compared and collated with each other. As a result, when it is determined that the face image of the person to be authenticated matches or resembles a registered face image of a certain registered person, the person to be authenticated is authenticated as the certain registered person.
In such an image collation device, due to differences in various photographing conditions between a face image of a person to be authenticated and a registered face image, the authentication rate may be reduced.
For example, when a direction in which light is illuminated to a face image of a person to be authenticated (hereinafter, this direction is referred to as an “illumination direction”) is different from an illumination direction of an object in the registered face image, even if the images are those of the same objects, as a result of comparison and collation, it may be determined that they do not match each other.
In order to solve these problems, various techniques have been proposed. For example, as to each of the registered persons, from one registered face image, an illumination direction at the photographing time and a face shape (normal vector (normal line vector)), and the like, are estimated. By using these conditions, a plurality of images in a plurality of different illumination directions (hereinafter, referred to as a “registered face image group”) are formed and registered in a database, and then at the time of authentication, a face image of an object is compared and collated with all the registered face image groups that have been registered in a database, thereby improving the authentication rate (see, for example, T. Sim, T. Kanade, “Combining Models and Exemplars for Face Recognition: An Illuminating Example,” Proc. CVPR Workshop on Models versus Exemplars in Computer Vision, 2001).
However, in the above-mentioned conventional technique, when an illumination direction in an image is estimated, the illumination direction is estimated assuming that all the reflection in the face is diffused reflection. Actually, however, since not all the reflection in a face is diffuse reflection, the directions of the normal vectors of the face may not be correctly estimated. Therefore, there is a problem that the formed registered face image group does not necessarily match an image actually photographed in a predetermined illumination direction. Even if authentication processing is carried out later, the authentication rate is not improved.